Overview

Dataset statistics

Number of variables18
Number of observations7346
Missing cells0
Missing cells (%)0.0%
Duplicate rows39
Duplicate rows (%)0.5%
Total size in memory1.1 MiB
Average record size in memory152.0 B

Variable types

Unsupported2
Numeric16

Alerts

Dataset has 39 (0.5%) duplicate rowsDuplicates
TOTAL_OIL_PROD is highly overall correlated with ACRES and 7 other fieldsHigh correlation
TOTAL_GAS_PROD is highly overall correlated with 2020_GAS_PROD and 5 other fieldsHigh correlation
ACRES is highly overall correlated with TOTAL_OIL_PROD and 1 other fieldsHigh correlation
TOTAL_WELLS is highly overall correlated with TOTAL_OIL_PROD and 4 other fieldsHigh correlation
2020_OIL_PROD is highly overall correlated with TOTAL_OIL_PROD and 5 other fieldsHigh correlation
2020_OIL_WELLS is highly overall correlated with TOTAL_OIL_PROD and 6 other fieldsHigh correlation
2020_GAS_PROD is highly overall correlated with TOTAL_GAS_PROD and 5 other fieldsHigh correlation
2020_GAS_WELLS is highly overall correlated with TOTAL_GAS_PROD and 5 other fieldsHigh correlation
2021_OIL_PROD is highly overall correlated with TOTAL_OIL_PROD and 5 other fieldsHigh correlation
2021_OIL_WELLS is highly overall correlated with TOTAL_OIL_PROD and 6 other fieldsHigh correlation
2021_GAS_PROD is highly overall correlated with TOTAL_GAS_PROD and 5 other fieldsHigh correlation
2021_GAS_WELLS is highly overall correlated with TOTAL_GAS_PROD and 5 other fieldsHigh correlation
2022_OIL_PROD is highly overall correlated with TOTAL_OIL_PROD and 5 other fieldsHigh correlation
2022_OIL_WELLS is highly overall correlated with TOTAL_OIL_PROD and 6 other fieldsHigh correlation
2022_GAS_PROD is highly overall correlated with TOTAL_GAS_PROD and 5 other fieldsHigh correlation
2022_GAS_WELLS is highly overall correlated with TOTAL_GAS_PROD and 5 other fieldsHigh correlation
TOTAL_OIL_PROD is highly skewed (γ1 = 29.30878156)Skewed
TOTAL_GAS_PROD is highly skewed (γ1 = 83.11992035)Skewed
ACRES is highly skewed (γ1 = 53.96694092)Skewed
TOTAL_WELLS is highly skewed (γ1 = 43.83043239)Skewed
2020_OIL_PROD is highly skewed (γ1 = 22.43657098)Skewed
2020_OIL_WELLS is highly skewed (γ1 = 42.55877372)Skewed
2020_GAS_PROD is highly skewed (γ1 = 75.10351662)Skewed
2020_GAS_WELLS is highly skewed (γ1 = 63.53279499)Skewed
2021_OIL_PROD is highly skewed (γ1 = 21.53532676)Skewed
2021_OIL_WELLS is highly skewed (γ1 = 42.2894771)Skewed
2021_GAS_PROD is highly skewed (γ1 = 75.43178121)Skewed
2021_GAS_WELLS is highly skewed (γ1 = 63.60517581)Skewed
2022_OIL_PROD is highly skewed (γ1 = 21.61944969)Skewed
2022_OIL_WELLS is highly skewed (γ1 = 41.36102384)Skewed
2022_GAS_PROD is highly skewed (γ1 = 75.3717434)Skewed
2022_GAS_WELLS is highly skewed (γ1 = 64.33845093)Skewed
PROD_ZONES is an unsupported type, check if it needs cleaning or further analysisUnsupported
DISCOVERY is an unsupported type, check if it needs cleaning or further analysisUnsupported
TOTAL_OIL_PROD has 709 (9.7%) zerosZeros
TOTAL_GAS_PROD has 5549 (75.5%) zerosZeros
ACRES has 355 (4.8%) zerosZeros
2020_OIL_PROD has 3447 (46.9%) zerosZeros
2020_OIL_WELLS has 3447 (46.9%) zerosZeros
2020_GAS_PROD has 6600 (89.8%) zerosZeros
2020_GAS_WELLS has 6600 (89.8%) zerosZeros
2021_OIL_PROD has 3458 (47.1%) zerosZeros
2021_OIL_WELLS has 3458 (47.1%) zerosZeros
2021_GAS_PROD has 6620 (90.1%) zerosZeros
2021_GAS_WELLS has 6620 (90.1%) zerosZeros
2022_OIL_PROD has 3566 (48.5%) zerosZeros
2022_OIL_WELLS has 3566 (48.5%) zerosZeros
2022_GAS_PROD has 6643 (90.4%) zerosZeros
2022_GAS_WELLS has 6643 (90.4%) zerosZeros

Reproduction

Analysis started2022-12-30 20:41:21.981891
Analysis finished2022-12-30 20:42:08.006446
Duration46.02 seconds
Software versionpandas-profiling vv3.6.1
Download configurationconfig.json

Variables

PROD_ZONES
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size114.8 KiB

DISCOVERY
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size114.8 KiB

TOTAL_OIL_PROD
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct6442
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean857357.67
Minimum0
Maximum3.1542562 × 108
Zeros709
Zeros (%)9.7%
Negative0
Negative (%)0.0%
Memory size114.8 KiB
2022-12-30T20:42:08.101756image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16285.5
median54744.5
Q3258251.75
95-th percentile2235490.5
Maximum3.1542562 × 108
Range3.1542562 × 108
Interquartile range (IQR)251966.25

Descriptive statistics

Standard deviation8178620.1
Coefficient of variation (CV)9.5393327
Kurtosis1005.5754
Mean857357.67
Median Absolute Deviation (MAD)54559.5
Skewness29.308782
Sum6.2981495 × 109
Variance6.6889827 × 1013
MonotonicityNot monotonic
2022-12-30T20:42:08.370194image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 709
 
9.7%
3988 3
 
< 0.1%
1232 3
 
< 0.1%
5070 3
 
< 0.1%
127 3
 
< 0.1%
110 3
 
< 0.1%
326 3
 
< 0.1%
1124 3
 
< 0.1%
122 3
 
< 0.1%
1536 3
 
< 0.1%
Other values (6432) 6610
90.0%
ValueCountFrequency (%)
0 709
9.7%
4 1
 
< 0.1%
7 1
 
< 0.1%
9 1
 
< 0.1%
10 2
 
< 0.1%
12 2
 
< 0.1%
13 1
 
< 0.1%
18 2
 
< 0.1%
20 1
 
< 0.1%
21 2
 
< 0.1%
ValueCountFrequency (%)
315425623 1
< 0.1%
312016415 1
< 0.1%
288375292 1
< 0.1%
274796693 1
< 0.1%
165643536 1
< 0.1%
141205891 1
< 0.1%
100681887 1
< 0.1%
90881849 1
< 0.1%
88339149 1
< 0.1%
77181056 1
< 0.1%

TOTAL_GAS_PROD
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct1795
Distinct (%)24.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5608836.9
Minimum0
Maximum2.7037909 × 1010
Zeros5549
Zeros (%)75.5%
Negative0
Negative (%)0.0%
Memory size114.8 KiB
2022-12-30T20:42:08.600780image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2646902.2
Maximum2.7037909 × 1010
Range2.7037909 × 1010
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.1894594 × 108
Coefficient of variation (CV)56.864898
Kurtosis7030.3841
Mean5608836.9
Median Absolute Deviation (MAD)0
Skewness83.11992
Sum4.1202516 × 1010
Variance1.0172651 × 1017
MonotonicityNot monotonic
2022-12-30T20:42:08.837004image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5549
75.5%
2883 2
 
< 0.1%
2016 2
 
< 0.1%
27593 2
 
< 0.1%
2792717 1
 
< 0.1%
13419343 1
 
< 0.1%
276842 1
 
< 0.1%
105495 1
 
< 0.1%
6253999 1
 
< 0.1%
5494507 1
 
< 0.1%
Other values (1785) 1785
 
24.3%
ValueCountFrequency (%)
0 5549
75.5%
4 1
 
< 0.1%
30 1
 
< 0.1%
55 1
 
< 0.1%
64 1
 
< 0.1%
86 1
 
< 0.1%
97 1
 
< 0.1%
143 1
 
< 0.1%
157 1
 
< 0.1%
177 1
 
< 0.1%
ValueCountFrequency (%)
2.703790933 × 10101
< 0.1%
3596589571 1
< 0.1%
1235684574 1
< 0.1%
896045276 1
< 0.1%
474795069 1
< 0.1%
466349637 1
< 0.1%
422324126 1
< 0.1%
322203561 1
< 0.1%
265121892 1
< 0.1%
248412613 1
< 0.1%

ACRES
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct293
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3872.2448
Minimum0
Maximum7350400
Zeros355
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size114.8 KiB
2022-12-30T20:42:09.086775image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile40
Q1160
median560
Q3960
95-th percentile4380
Maximum7350400
Range7350400
Interquartile range (IQR)800

Descriptive statistics

Standard deviation109495.07
Coefficient of variation (CV)28.276898
Kurtosis3212.2591
Mean3872.2448
Median Absolute Deviation (MAD)400
Skewness53.966941
Sum28445510
Variance1.198917 × 1010
MonotonicityNot monotonic
2022-12-30T20:42:09.312439image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
160 1876
25.5%
640 1298
17.7%
320 821
11.2%
960 364
 
5.0%
480 361
 
4.9%
0 355
 
4.8%
800 335
 
4.6%
1120 170
 
2.3%
1280 146
 
2.0%
1440 123
 
1.7%
Other values (283) 1497
20.4%
ValueCountFrequency (%)
0 355
 
4.8%
10 1
 
< 0.1%
40 31
 
0.4%
50 1
 
< 0.1%
80 30
 
0.4%
100 1
 
< 0.1%
120 8
 
0.1%
160 1876
25.5%
170 1
 
< 0.1%
200 18
 
0.2%
ValueCountFrequency (%)
7350400 1
< 0.1%
4377600 1
< 0.1%
3060480 1
< 0.1%
2254080 1
< 0.1%
325760 1
< 0.1%
300960 1
< 0.1%
243840 1
< 0.1%
192000 1
< 0.1%
172160 1
< 0.1%
121440 1
< 0.1%

TOTAL_WELLS
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct323
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.305745
Minimum0
Maximum20840
Zeros37
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size114.8 KiB
2022-12-30T20:42:09.567909image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median8
Q320
95-th percentile94
Maximum20840
Range20840
Interquartile range (IQR)18

Descriptive statistics

Standard deviation324.83183
Coefficient of variation (CV)8.9471193
Kurtosis2488.9845
Mean36.305745
Median Absolute Deviation (MAD)6
Skewness43.830432
Sum266702
Variance105515.72
MonotonicityNot monotonic
2022-12-30T20:42:09.784220image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1112
 
15.1%
2 689
 
9.4%
3 510
 
6.9%
4 428
 
5.8%
5 307
 
4.2%
6 290
 
3.9%
8 261
 
3.6%
7 249
 
3.4%
9 225
 
3.1%
10 188
 
2.6%
Other values (313) 3087
42.0%
ValueCountFrequency (%)
0 37
 
0.5%
1 1112
15.1%
2 689
9.4%
3 510
6.9%
4 428
 
5.8%
5 307
 
4.2%
6 290
 
3.9%
7 249
 
3.4%
8 261
 
3.6%
9 225
 
3.1%
ValueCountFrequency (%)
20840 1
< 0.1%
10459 1
< 0.1%
6719 1
< 0.1%
5427 1
< 0.1%
5407 1
< 0.1%
4158 1
< 0.1%
3310 1
< 0.1%
3294 1
< 0.1%
3206 1
< 0.1%
2827 1
< 0.1%

2020_OIL_PROD
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct2585
Distinct (%)35.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3105.8064
Minimum0
Maximum724131
Zeros3447
Zeros (%)46.9%
Negative0
Negative (%)0.0%
Memory size114.8 KiB
2022-12-30T20:42:10.004947image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median160
Q31767.5
95-th percentile10908
Maximum724131
Range724131
Interquartile range (IQR)1767.5

Descriptive statistics

Standard deviation17724.923
Coefficient of variation (CV)5.7070277
Kurtosis691.54909
Mean3105.8064
Median Absolute Deviation (MAD)160
Skewness22.436571
Sum22815254
Variance3.1417291 × 108
MonotonicityNot monotonic
2022-12-30T20:42:10.226570image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3447
46.9%
160 19
 
0.3%
319 18
 
0.2%
157 18
 
0.2%
155 17
 
0.2%
162 17
 
0.2%
159 16
 
0.2%
163 14
 
0.2%
154 14
 
0.2%
323 13
 
0.2%
Other values (2575) 3753
51.1%
ValueCountFrequency (%)
0 3447
46.9%
1 1
 
< 0.1%
3 1
 
< 0.1%
5 2
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
9 2
 
< 0.1%
11 2
 
< 0.1%
14 1
 
< 0.1%
ValueCountFrequency (%)
724131 1
< 0.1%
608746 1
< 0.1%
437990 1
< 0.1%
365765 1
< 0.1%
327338 1
< 0.1%
321006 1
< 0.1%
263588 1
< 0.1%
260347 1
< 0.1%
231215 1
< 0.1%
229821 1
< 0.1%

2020_OIL_WELLS
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct146
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.2726654
Minimum0
Maximum3944
Zeros3447
Zeros (%)46.9%
Negative0
Negative (%)0.0%
Memory size114.8 KiB
2022-12-30T20:42:10.472034image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile15
Maximum3944
Range3944
Interquartile range (IQR)2

Descriptive statistics

Standard deviation60.743125
Coefficient of variation (CV)9.6837822
Kurtosis2494.6977
Mean6.2726654
Median Absolute Deviation (MAD)1
Skewness42.558774
Sum46079
Variance3689.7273
MonotonicityNot monotonic
2022-12-30T20:42:10.712754image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3447
46.9%
1 1393
19.0%
2 686
 
9.3%
3 423
 
5.8%
4 245
 
3.3%
5 187
 
2.5%
6 146
 
2.0%
7 103
 
1.4%
8 87
 
1.2%
10 62
 
0.8%
Other values (136) 567
 
7.7%
ValueCountFrequency (%)
0 3447
46.9%
1 1393
19.0%
2 686
 
9.3%
3 423
 
5.8%
4 245
 
3.3%
5 187
 
2.5%
6 146
 
2.0%
7 103
 
1.4%
8 87
 
1.2%
9 59
 
0.8%
ValueCountFrequency (%)
3944 1
< 0.1%
1358 1
< 0.1%
1283 1
< 0.1%
997 1
< 0.1%
974 1
< 0.1%
683 1
< 0.1%
650 1
< 0.1%
606 1
< 0.1%
575 1
< 0.1%
556 1
< 0.1%

2020_GAS_PROD
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct738
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21076.549
Minimum0
Maximum76710262
Zeros6600
Zeros (%)89.8%
Negative0
Negative (%)0.0%
Memory size114.8 KiB
2022-12-30T20:42:10.972224image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile15190.5
Maximum76710262
Range76710262
Interquartile range (IQR)0

Descriptive statistics

Standard deviation943342.36
Coefficient of variation (CV)44.757914
Kurtosis5988.9416
Mean21076.549
Median Absolute Deviation (MAD)0
Skewness75.103517
Sum1.5482833 × 108
Variance8.8989481 × 1011
MonotonicityNot monotonic
2022-12-30T20:42:11.207316image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6600
89.8%
1293 2
 
< 0.1%
6302 2
 
< 0.1%
1408 2
 
< 0.1%
4757 2
 
< 0.1%
14548 2
 
< 0.1%
13053 2
 
< 0.1%
1376 2
 
< 0.1%
36 2
 
< 0.1%
11 2
 
< 0.1%
Other values (728) 728
 
9.9%
ValueCountFrequency (%)
0 6600
89.8%
2 1
 
< 0.1%
3 1
 
< 0.1%
5 1
 
< 0.1%
10 1
 
< 0.1%
11 2
 
< 0.1%
22 1
 
< 0.1%
25 1
 
< 0.1%
26 1
 
< 0.1%
36 2
 
< 0.1%
ValueCountFrequency (%)
76710262 1
< 0.1%
21371115 1
< 0.1%
12889388 1
< 0.1%
3322798 1
< 0.1%
2877494 1
< 0.1%
1400150 1
< 0.1%
1209335 1
< 0.1%
1014689 1
< 0.1%
964333 1
< 0.1%
943960 1
< 0.1%

2020_GAS_WELLS
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct60
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6754696
Minimum0
Maximum7278
Zeros6600
Zeros (%)89.8%
Negative0
Negative (%)0.0%
Memory size114.8 KiB
2022-12-30T20:42:11.434126image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum7278
Range7278
Interquartile range (IQR)0

Descriptive statistics

Standard deviation97.63318
Coefficient of variation (CV)36.491978
Kurtosis4427.8498
Mean2.6754696
Median Absolute Deviation (MAD)0
Skewness63.532795
Sum19654
Variance9532.2378
MonotonicityNot monotonic
2022-12-30T20:42:11.677900image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6600
89.8%
1 276
 
3.8%
2 116
 
1.6%
3 68
 
0.9%
4 44
 
0.6%
5 41
 
0.6%
6 28
 
0.4%
7 23
 
0.3%
8 16
 
0.2%
9 12
 
0.2%
Other values (50) 122
 
1.7%
ValueCountFrequency (%)
0 6600
89.8%
1 276
 
3.8%
2 116
 
1.6%
3 68
 
0.9%
4 44
 
0.6%
5 41
 
0.6%
6 28
 
0.4%
7 23
 
0.3%
8 16
 
0.2%
9 12
 
0.2%
ValueCountFrequency (%)
7278 1
< 0.1%
3395 1
< 0.1%
2128 1
< 0.1%
637 1
< 0.1%
530 1
< 0.1%
232 1
< 0.1%
211 1
< 0.1%
183 1
< 0.1%
155 1
< 0.1%
154 1
< 0.1%

2021_OIL_PROD
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct2617
Distinct (%)35.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3056.5494
Minimum0
Maximum702299
Zeros3458
Zeros (%)47.1%
Negative0
Negative (%)0.0%
Memory size114.8 KiB
2022-12-30T20:42:11.903491image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median161
Q31760
95-th percentile10536.75
Maximum702299
Range702299
Interquartile range (IQR)1760

Descriptive statistics

Standard deviation17090.108
Coefficient of variation (CV)5.5913077
Kurtosis639.93597
Mean3056.5494
Median Absolute Deviation (MAD)161
Skewness21.535327
Sum22453412
Variance2.920718 × 108
MonotonicityNot monotonic
2022-12-30T20:42:12.124840image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3458
47.1%
156 14
 
0.2%
158 14
 
0.2%
160 14
 
0.2%
323 12
 
0.2%
154 12
 
0.2%
316 12
 
0.2%
320 11
 
0.1%
314 11
 
0.1%
162 11
 
0.1%
Other values (2607) 3777
51.4%
ValueCountFrequency (%)
0 3458
47.1%
3 1
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
10 4
 
0.1%
11 1
 
< 0.1%
12 1
 
< 0.1%
14 2
 
< 0.1%
15 2
 
< 0.1%
17 1
 
< 0.1%
ValueCountFrequency (%)
702299 1
< 0.1%
493005 1
< 0.1%
462485 1
< 0.1%
365661 1
< 0.1%
342608 1
< 0.1%
307978 1
< 0.1%
261994 1
< 0.1%
249033 1
< 0.1%
222628 1
< 0.1%
219720 1
< 0.1%

2021_OIL_WELLS
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct139
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.1463381
Minimum0
Maximum3889
Zeros3458
Zeros (%)47.1%
Negative0
Negative (%)0.0%
Memory size114.8 KiB
2022-12-30T20:42:12.382170image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile14
Maximum3889
Range3889
Interquartile range (IQR)2

Descriptive statistics

Standard deviation60.19943
Coefficient of variation (CV)9.794357
Kurtosis2455.047
Mean6.1463381
Median Absolute Deviation (MAD)1
Skewness42.289477
Sum45151
Variance3623.9714
MonotonicityNot monotonic
2022-12-30T20:42:12.614381image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3458
47.1%
1 1416
19.3%
2 695
 
9.5%
3 409
 
5.6%
4 254
 
3.5%
5 189
 
2.6%
6 117
 
1.6%
7 114
 
1.6%
9 67
 
0.9%
8 66
 
0.9%
Other values (129) 561
 
7.6%
ValueCountFrequency (%)
0 3458
47.1%
1 1416
19.3%
2 695
 
9.5%
3 409
 
5.6%
4 254
 
3.5%
5 189
 
2.6%
6 117
 
1.6%
7 114
 
1.6%
8 66
 
0.9%
9 67
 
0.9%
ValueCountFrequency (%)
3889 1
< 0.1%
1375 1
< 0.1%
1315 1
< 0.1%
1018 1
< 0.1%
977 1
< 0.1%
668 1
< 0.1%
638 1
< 0.1%
628 1
< 0.1%
589 1
< 0.1%
577 1
< 0.1%

2021_GAS_PROD
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct721
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19765.939
Minimum0
Maximum72056862
Zeros6620
Zeros (%)90.1%
Negative0
Negative (%)0.0%
Memory size114.8 KiB
2022-12-30T20:42:12.869435image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile14343.25
Maximum72056862
Range72056862
Interquartile range (IQR)0

Descriptive statistics

Standard deviation884484.28
Coefficient of variation (CV)44.747901
Kurtosis6031.372
Mean19765.939
Median Absolute Deviation (MAD)0
Skewness75.431781
Sum1.4520059 × 108
Variance7.8231244 × 1011
MonotonicityNot monotonic
2022-12-30T20:42:13.373551image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6620
90.1%
43777 2
 
< 0.1%
2942 2
 
< 0.1%
22646 2
 
< 0.1%
6924 2
 
< 0.1%
55897 2
 
< 0.1%
41786 2
 
< 0.1%
10305 1
 
< 0.1%
18236 1
 
< 0.1%
59179 1
 
< 0.1%
Other values (711) 711
 
9.7%
ValueCountFrequency (%)
0 6620
90.1%
1 1
 
< 0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
12 1
 
< 0.1%
16 1
 
< 0.1%
17 1
 
< 0.1%
25 1
 
< 0.1%
32 1
 
< 0.1%
33 1
 
< 0.1%
ValueCountFrequency (%)
72056862 1
< 0.1%
19946514 1
< 0.1%
11378674 1
< 0.1%
3286459 1
< 0.1%
2645673 1
< 0.1%
1238971 1
< 0.1%
1084027 1
< 0.1%
1024850 1
< 0.1%
1017172 1
< 0.1%
992857 1
< 0.1%

2021_GAS_WELLS
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct61
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5997822
Minimum0
Maximum7209
Zeros6620
Zeros (%)90.1%
Negative0
Negative (%)0.0%
Memory size114.8 KiB
2022-12-30T20:42:13.600985image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum7209
Range7209
Interquartile range (IQR)0

Descriptive statistics

Standard deviation96.681466
Coefficient of variation (CV)37.188294
Kurtosis4434.1976
Mean2.5997822
Median Absolute Deviation (MAD)0
Skewness63.605176
Sum19098
Variance9347.3058
MonotonicityNot monotonic
2022-12-30T20:42:13.826403image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6620
90.1%
1 278
 
3.8%
2 104
 
1.4%
3 72
 
1.0%
4 36
 
0.5%
5 36
 
0.5%
6 35
 
0.5%
7 27
 
0.4%
11 14
 
0.2%
9 12
 
0.2%
Other values (51) 112
 
1.5%
ValueCountFrequency (%)
0 6620
90.1%
1 278
 
3.8%
2 104
 
1.4%
3 72
 
1.0%
4 36
 
0.5%
5 36
 
0.5%
6 35
 
0.5%
7 27
 
0.4%
8 9
 
0.1%
9 12
 
0.2%
ValueCountFrequency (%)
7209 1
< 0.1%
3372 1
< 0.1%
2095 1
< 0.1%
621 1
< 0.1%
529 1
< 0.1%
232 1
< 0.1%
206 1
< 0.1%
173 1
< 0.1%
137 1
< 0.1%
136 1
< 0.1%

2022_OIL_PROD
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct2088
Distinct (%)28.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1709.8492
Minimum0
Maximum406933
Zeros3566
Zeros (%)48.5%
Negative0
Negative (%)0.0%
Memory size114.8 KiB
2022-12-30T20:42:14.083967image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median146
Q3970
95-th percentile5923
Maximum406933
Range406933
Interquartile range (IQR)970

Descriptive statistics

Standard deviation9388.2567
Coefficient of variation (CV)5.4906929
Kurtosis673.93277
Mean1709.8492
Median Absolute Deviation (MAD)146
Skewness21.61945
Sum12560552
Variance88139364
MonotonicityNot monotonic
2022-12-30T20:42:14.311971image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3566
48.5%
161 29
 
0.4%
159 26
 
0.4%
158 26
 
0.4%
162 24
 
0.3%
320 23
 
0.3%
160 22
 
0.3%
157 21
 
0.3%
318 21
 
0.3%
156 21
 
0.3%
Other values (2078) 3567
48.6%
ValueCountFrequency (%)
0 3566
48.5%
3 2
 
< 0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
8 3
 
< 0.1%
13 3
 
< 0.1%
19 1
 
< 0.1%
20 1
 
< 0.1%
24 2
 
< 0.1%
25 1
 
< 0.1%
ValueCountFrequency (%)
406933 1
< 0.1%
255959 1
< 0.1%
212822 1
< 0.1%
193025 1
< 0.1%
176385 1
< 0.1%
172920 1
< 0.1%
150854 1
< 0.1%
133788 1
< 0.1%
129840 1
< 0.1%
129750 1
< 0.1%

2022_OIL_WELLS
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct138
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.8674108
Minimum0
Maximum3639
Zeros3566
Zeros (%)48.5%
Negative0
Negative (%)0.0%
Memory size114.8 KiB
2022-12-30T20:42:14.571635image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile13
Maximum3639
Range3639
Interquartile range (IQR)2

Descriptive statistics

Standard deviation56.906842
Coefficient of variation (CV)9.6987996
Kurtosis2363.5849
Mean5.8674108
Median Absolute Deviation (MAD)1
Skewness41.361024
Sum43102
Variance3238.3887
MonotonicityNot monotonic
2022-12-30T20:42:14.798202image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3566
48.5%
1 1374
 
18.7%
2 704
 
9.6%
3 385
 
5.2%
4 262
 
3.6%
5 164
 
2.2%
6 126
 
1.7%
7 108
 
1.5%
9 65
 
0.9%
8 59
 
0.8%
Other values (128) 533
 
7.3%
ValueCountFrequency (%)
0 3566
48.5%
1 1374
 
18.7%
2 704
 
9.6%
3 385
 
5.2%
4 262
 
3.6%
5 164
 
2.2%
6 126
 
1.7%
7 108
 
1.5%
8 59
 
0.8%
9 65
 
0.9%
ValueCountFrequency (%)
3639 1
< 0.1%
1279 1
< 0.1%
1262 1
< 0.1%
1010 1
< 0.1%
931 1
< 0.1%
658 1
< 0.1%
614 1
< 0.1%
582 1
< 0.1%
567 1
< 0.1%
561 1
< 0.1%

2022_GAS_PROD
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct695
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11065.357
Minimum0
Maximum40152740
Zeros6643
Zeros (%)90.4%
Negative0
Negative (%)0.0%
Memory size114.8 KiB
2022-12-30T20:42:15.067572image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile7748
Maximum40152740
Range40152740
Interquartile range (IQR)0

Descriptive statistics

Standard deviation493039.49
Coefficient of variation (CV)44.557034
Kurtosis6023.5201
Mean11065.357
Median Absolute Deviation (MAD)0
Skewness75.371743
Sum81286112
Variance2.4308794 × 1011
MonotonicityNot monotonic
2022-12-30T20:42:15.307729image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6643
90.4%
3429 3
 
< 0.1%
4 2
 
< 0.1%
2 2
 
< 0.1%
14 2
 
< 0.1%
3848 2
 
< 0.1%
3882 2
 
< 0.1%
6219 2
 
< 0.1%
2115 2
 
< 0.1%
2457 1
 
< 0.1%
Other values (685) 685
 
9.3%
ValueCountFrequency (%)
0 6643
90.4%
2 2
 
< 0.1%
4 2
 
< 0.1%
6 1
 
< 0.1%
10 1
 
< 0.1%
11 1
 
< 0.1%
14 2
 
< 0.1%
16 1
 
< 0.1%
31 1
 
< 0.1%
34 1
 
< 0.1%
ValueCountFrequency (%)
40152740 1
< 0.1%
11169613 1
< 0.1%
6297442 1
< 0.1%
2024499 1
< 0.1%
1438308 1
< 0.1%
643336 1
< 0.1%
599745 1
< 0.1%
574015 1
< 0.1%
541418 1
< 0.1%
540458 1
< 0.1%

2022_GAS_WELLS
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct57
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5397495
Minimum0
Maximum7154
Zeros6643
Zeros (%)90.4%
Negative0
Negative (%)0.0%
Memory size114.8 KiB
2022-12-30T20:42:15.572751image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum7154
Range7154
Interquartile range (IQR)0

Descriptive statistics

Standard deviation95.182763
Coefficient of variation (CV)37.477224
Kurtosis4541.4502
Mean2.5397495
Median Absolute Deviation (MAD)0
Skewness64.338451
Sum18657
Variance9059.7583
MonotonicityNot monotonic
2022-12-30T20:42:15.808895image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6643
90.4%
1 267
 
3.6%
2 104
 
1.4%
3 69
 
0.9%
4 37
 
0.5%
6 35
 
0.5%
7 31
 
0.4%
5 28
 
0.4%
8 11
 
0.1%
9 10
 
0.1%
Other values (47) 111
 
1.5%
ValueCountFrequency (%)
0 6643
90.4%
1 267
 
3.6%
2 104
 
1.4%
3 69
 
0.9%
4 37
 
0.5%
5 28
 
0.4%
6 35
 
0.5%
7 31
 
0.4%
8 11
 
0.1%
9 10
 
0.1%
ValueCountFrequency (%)
7154 1
< 0.1%
3192 1
< 0.1%
2066 1
< 0.1%
616 1
< 0.1%
532 1
< 0.1%
232 1
< 0.1%
202 1
< 0.1%
165 1
< 0.1%
134 1
< 0.1%
127 1
< 0.1%

Interactions

2022-12-30T20:42:03.524718image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:22.457454image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:25.914970image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:29.493665image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:32.678188image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:34.999609image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:37.567876image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:40.382139image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:43.032991image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:45.493194image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:48.152775image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:50.856407image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:53.357466image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:55.669306image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:58.351868image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:00.751344image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:03.727488image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:22.695869image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:26.126923image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:29.716552image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:32.820276image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:35.149643image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:37.729400image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:40.560908image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:43.180832image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:45.632176image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:48.299073image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:51.019628image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:53.494272image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:55.816917image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:58.502763image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:00.907637image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:03.966885image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:22.911105image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:26.321284image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:29.922152image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:32.951535image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:35.297402image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:38.108029image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:40.741778image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:43.364861image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:45.780628image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:48.450483image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:51.177579image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:53.630978image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:55.972547image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:58.643396image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:01.047662image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:04.183806image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:23.122940image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:26.571178image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:30.132933image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:33.099205image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:35.444481image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:38.276556image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:40.927276image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:43.507270image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:45.928504image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:48.615636image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:51.353976image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:53.777900image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:56.127384image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:58.789980image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:01.201044image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:04.375365image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:23.313579image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:26.727227image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:30.325596image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:33.226386image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:35.588761image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:38.422657image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:41.064513image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:43.642548image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:46.060265image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:48.797459image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:51.491833image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:53.914821image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:56.264168image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:58.926537image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:01.332738image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:04.587137image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:23.525518image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:26.930334image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:30.574174image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:33.366841image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:35.760430image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:38.580629image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:41.262410image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:43.797693image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:46.207846image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:49.017985image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:51.644539image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:54.062682image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:56.420598image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:59.074703image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:01.479806image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:04.797646image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:23.774072image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:27.319023image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:30.788810image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:33.519481image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:35.943492image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:38.744406image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:41.429371image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:43.957294image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:46.357722image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:49.177730image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:51.806646image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:54.210277image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:56.844721image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:59.228346image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:01.631226image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:05.020990image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:23.983311image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:27.525530image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:30.996999image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:33.669312image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:36.176501image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:38.911427image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:41.585804image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:44.103704image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:46.510785image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:49.334040image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:51.965999image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:54.352704image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:57.003868image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:59.388034image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:01.781774image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:05.225607image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:24.194095image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:27.728926image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:31.205097image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:33.822121image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:36.331222image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:39.064163image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:41.741395image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:44.247336image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:46.663121image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:49.485176image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:52.122031image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:54.493642image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:57.147607image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:59.537822image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:01.927364image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:05.432601image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:24.401546image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:27.976639image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:31.419760image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:33.965366image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:36.482688image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:39.222489image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:41.904762image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:44.400069image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:46.818844image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:49.636789image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:52.288605image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:54.638685image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:57.295588image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:59.722747image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:02.075813image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:05.682380image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:24.622073image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:28.188082image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:31.667501image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:34.118205image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:36.639567image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:39.390054image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:42.076349image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:44.560036image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:47.227712image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:49.809062image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:52.446790image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:54.790901image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:57.452427image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:59.879120image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:02.221224image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:05.894582image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:24.835600image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:28.395611image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:31.882694image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:34.254764image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:36.798927image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:39.560837image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:42.244839image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:44.723912image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:47.384598image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:50.004446image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:52.596893image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:54.947483image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:57.605710image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:00.031024image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:02.436518image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:06.108908image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:25.070026image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:28.607611image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:32.097833image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:34.398953image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:36.954435image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:39.731110image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:42.413673image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:44.880592image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:47.539622image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:50.198774image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:52.738947image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:55.090536image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:57.751683image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:00.170548image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:02.672405image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:06.316625image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:25.282945image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:28.825352image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:32.249346image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:34.554902image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:37.114446image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:39.898246image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:42.563440image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:45.035418image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:47.695981image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:50.364573image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:52.899678image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:55.240475image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:57.908089image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:00.312500image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:02.883044image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:06.522614image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:25.492340image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:29.068302image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:32.389116image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:34.703885image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:37.265081image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:40.046520image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:42.725937image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:45.190481image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:47.846602image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:50.519697image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:53.050508image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:55.383052image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:58.055715image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:00.452197image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:03.096296image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:06.769685image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:25.705721image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:29.271493image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:32.535339image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:34.855337image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:37.421762image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:40.217612image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:42.880369image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:45.347107image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:48.005450image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:50.684879image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:53.217488image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:55.527390image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:41:58.207097image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:00.607955image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-30T20:42:03.312006image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Correlations

2022-12-30T20:42:16.032499image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
TOTAL_OIL_PRODTOTAL_GAS_PRODACRESTOTAL_WELLS2020_OIL_PROD2020_OIL_WELLS2020_GAS_PROD2020_GAS_WELLS2021_OIL_PROD2021_OIL_WELLS2021_GAS_PROD2021_GAS_WELLS2022_OIL_PROD2022_OIL_WELLS2022_GAS_PROD2022_GAS_WELLS
TOTAL_OIL_PROD1.0000.0490.5620.7870.7170.7390.0970.0990.7180.7360.0990.1010.7120.7260.1030.106
TOTAL_GAS_PROD0.0491.0000.3600.2600.0050.0350.6600.6600.0010.0280.6510.6510.0050.0280.6420.642
ACRES0.5620.3601.0000.7320.3740.4340.2740.2770.3770.4320.2730.2750.3800.4260.2720.274
TOTAL_WELLS0.7870.2600.7321.0000.4760.5500.2040.2080.4800.5490.2050.2090.4810.5410.2070.210
2020_OIL_PROD0.7170.0050.3740.4761.0000.9470.1000.1010.9680.9170.1000.1010.9500.9100.1020.104
2020_OIL_WELLS0.7390.0350.4340.5500.9471.0000.1120.1140.9140.9520.1110.1130.9010.9380.1150.117
2020_GAS_PROD0.0970.6600.2740.2040.1000.1121.0000.9990.0940.1050.9640.9630.0970.1050.9400.938
2020_GAS_WELLS0.0990.6600.2770.2080.1010.1140.9991.0000.0960.1080.9610.9610.0990.1080.9360.936
2021_OIL_PROD0.7180.0010.3770.4800.9680.9140.0940.0961.0000.9500.0980.0990.9650.9220.1000.102
2021_OIL_WELLS0.7360.0280.4320.5490.9170.9520.1050.1080.9501.0000.1080.1100.9120.9490.1120.114
2021_GAS_PROD0.0990.6510.2730.2050.1000.1110.9640.9610.0980.1081.0000.9990.0990.1070.9660.965
2021_GAS_WELLS0.1010.6510.2750.2090.1010.1130.9630.9610.0990.1100.9991.0000.1010.1090.9630.964
2022_OIL_PROD0.7120.0050.3800.4810.9500.9010.0970.0990.9650.9120.0990.1011.0000.9540.1030.105
2022_OIL_WELLS0.7260.0280.4260.5410.9100.9380.1050.1080.9220.9490.1070.1090.9541.0000.1120.114
2022_GAS_PROD0.1030.6420.2720.2070.1020.1150.9400.9360.1000.1120.9660.9630.1030.1121.0000.999
2022_GAS_WELLS0.1060.6420.2740.2100.1040.1170.9380.9360.1020.1140.9650.9640.1050.1140.9991.000

Missing values

2022-12-30T20:42:07.279321image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
A simple visualization of nullity by column.
2022-12-30T20:42:07.782350image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

PROD_ZONESDISCOVERYTOTAL_OIL_PRODTOTAL_GAS_PRODACRESTOTAL_WELLS2020_OIL_PROD2020_OIL_WELLS2020_GAS_PROD2020_GAS_WELLS2021_OIL_PROD2021_OIL_WELLS2021_GAS_PROD2021_GAS_WELLS2022_OIL_PROD2022_OIL_WELLS2022_GAS_PROD2022_GAS_WELLS
FIELD_NAME
A&WLANSING-KANSAS CITY, MARMATON, CHEROKEE, MISSISSIPPIAN1981-10-01 00:00:00145594.0260239.01280.016155.01.00.00.00.00.00.00.0152.01.00.00.0
ABBYVILLELANSING-KANSAS CITY1927-01-01 00:00:001193376.00.02240.0490.00.00.00.00.00.00.00.00.00.00.00.0
ABBYVILLE NORTHEASTLANSING-KANSAS CITY1982-06-01 00:00:00108964.00.0320.041465.02.00.00.01458.02.00.00.0777.02.00.00.0
ACRESMISSISSIPPIAN1984-02-01 00:00:002069.0770476.0800.050.00.010332.02.094.01.012977.02.00.00.09299.02.0
ACRES SOUTHMISSISSIPPIAN1984-02-01 00:00:000.013499.0160.020.00.00.00.00.00.00.00.00.00.00.00.0
Acres WestMARMATON, MORROWAN, MISSISSIPPIAN1984-02-01 00:00:004673.04005962.0960.090.00.034016.04.00.00.033512.04.00.00.017887.03.0
ADAIRLANSING-KANSAS CITY, MARMATON, ARBUCKLE1953-01-01 00:00:00470535.00.0640.0241461.08.00.00.02596.08.00.00.01620.08.00.00.0
ADAIR NORTHWESTLANSING-KANSAS CITY, ARBUCKLE1985-01-01 00:00:0029302.00.0160.04480.01.00.00.0654.01.00.00.0328.01.00.00.0
ADAIR SOUTHWESTMARMATON1956-01-01 00:00:0017386.00.0560.0120.00.00.00.00.00.00.00.00.00.00.00.0
ADAMSLAYTON, MARMATON, CATTLEMAN, BURGESS, ARBUCKLE1954-01-01 00:00:0046176.01325132.04320.0280.00.00.00.00.00.00.00.00.00.00.00.0
PROD_ZONESDISCOVERYTOTAL_OIL_PRODTOTAL_GAS_PRODACRESTOTAL_WELLS2020_OIL_PROD2020_OIL_WELLS2020_GAS_PROD2020_GAS_WELLS2021_OIL_PROD2021_OIL_WELLS2021_GAS_PROD2021_GAS_WELLS2022_OIL_PROD2022_OIL_WELLS2022_GAS_PROD2022_GAS_WELLS
FIELD_NAME
ZUERCHERLANSING-KANSAS CITY, MISSISSIPPIAN, SIMPSON1959-07-01 00:00:00804419.0232046.0800.0230.00.00.00.00.00.00.00.00.00.00.00.0
ZurichSHAWNEE GROUP, LANSING-KANSAS CITY1935-09-01 00:00:001681261.00.01440.04812989.011.00.00.012808.011.00.00.07249.011.00.00.0
ZURICH TOWNSITESHAWNEE GROUP, LANSING-KANSAS CITY, ARBUCKLE1944-02-01 00:00:001857173.00.0800.03910504.011.00.00.09860.011.00.00.05442.011.00.00.0
ZURICH TOWNSITE SOUTHSHAWNEE GROUP, LANSING-KANSAS CITY, ARBUCKLE1949-01-01 00:00:00199439.00.0320.0182133.01.00.00.02766.01.00.00.01142.01.00.00.0
ZURICH TOWNSITE SOUTHEASTLANSING-KANSAS CITY1978-07-01 00:00:0079905.00.0640.08302.01.00.00.0310.01.00.00.0304.01.00.00.0
ZURICH TOWNSITE WESTLANSING-KANSAS CITY, ARBUCKLE1977-06-01 00:00:0081493.00.0320.015265.01.00.00.0324.01.00.00.0498.01.00.00.0
ZWAHLENCHEROKEE1994-01-01 00:00:000.081948.0320.0130.00.00.00.00.00.00.00.00.00.00.00.0
ZweygardtLansing-Kansas City2004-01-01 00:00:0072842.00.0160.041428.03.00.00.01883.03.00.00.01249.03.00.00.0
ZYBASIMPSON1937-10-01 00:00:00983201.00.0960.032674.01.00.00.01030.02.00.00.0487.02.00.00.0
ZYBA SOUTHWESTLANSING-KANSAS CITY, SIMPSON1944-06-01 00:00:001897837.00.0800.0430.00.00.00.00.00.00.00.00.00.00.00.0

Duplicate rows

Most frequently occurring

TOTAL_OIL_PRODTOTAL_GAS_PRODACRESTOTAL_WELLS2020_OIL_PROD2020_OIL_WELLS2020_GAS_PROD2020_GAS_WELLS2021_OIL_PROD2021_OIL_WELLS2021_GAS_PROD2021_GAS_WELLS2022_OIL_PROD2022_OIL_WELLS2022_GAS_PROD2022_GAS_WELLS# duplicates
10.00.00.010.00.00.00.00.00.00.00.00.00.00.00.0110
70.00.0160.010.00.00.00.00.00.00.00.00.00.00.00.0101
80.00.0160.020.00.00.00.00.00.00.00.00.00.00.00.044
210.00.0640.010.00.00.00.00.00.00.00.00.00.00.00.044
00.00.00.000.00.00.00.00.00.00.00.00.00.00.00.012
130.00.0320.010.00.00.00.00.00.00.00.00.00.00.00.011
140.00.0320.020.00.00.00.00.00.00.00.00.00.00.00.010
20.00.00.020.00.00.00.00.00.00.00.00.00.00.00.09
90.00.0160.030.00.00.00.00.00.00.00.00.00.00.00.09
100.00.0160.040.00.00.00.00.00.00.00.00.00.00.00.08